code: def get_fake_maskformer_outputs(self):
      return MaskFormerForInstanceSegmentationOutput(
          # +1 for null class
          class_queries_logits=torch.randn(
              (self.batch_size, self.num_queries, self.num_classes + 1)
          ),
          masks_queries_logits=torch.randn(
              (
                  self.batch_size,
                  self.num_queries,
                  self.height,
                  self.width,
              )
          ),
      )
  
imports: import unittest
  import numpy
  from transformers.testing_utils import require_torch, require_vision
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin, prepare_image_inputs
label_desc: Use image node_id 4 for calling the MaskFormerFeatureExtractionTester obj's underlying member method code with example usage: obj.get_fake_maskformer_outputs() and returns: MaskFormerForInstanceSegmentationOutput